Protein Homology Detection Through Alignment of Markov Random Fields
Using MRFalign
(Sprache: Englisch)
This work covers sequence-based protein homology detection, a fundamental and challenging bioinformatics problem with a variety of real-world applications. The text first surveys a few popular homology detection methods, such as Position-Specific Scoring...
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This work covers sequence-based protein homology detection, a fundamental and challenging bioinformatics problem with a variety of real-world applications. The text first surveys a few popular homology detection methods, such as Position-Specific Scoring Matrix (PSSM) and Hidden Markov Model (HMM) based methods, and then describes a novel Markov Random Fields (MRF) based method developed by the authors. MRF-based methods are much more sensitive than HMM- and PSSM-based methods for remote homolog detection and fold recognition, as MRFs can model long-range residue-residue interaction. The text also describes the installation, usage and result interpretation of programs implementing the MRF-based method.
Inhaltsverzeichnis zu „Protein Homology Detection Through Alignment of Markov Random Fields “
IntroductionMethod
Software
Experiments and Results
Conclusion
Bibliographische Angaben
- Autoren: Jinbo Xu , Jianzhu Ma , Sheng Wang
- 2015, 60 Seiten, Masse: 15,5 x 23,5 cm, Kartoniert (TB), Englisch
- Verlag: Springer International Publishing
- ISBN-10: 331914913X
- ISBN-13: 9783319149134
- Erscheinungsdatum: 03.03.2015
Sprache:
Englisch
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